Udacity Deep Learning Nanodegree Review

Udacity Deep Learning Nanodegree Review
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Learn how to create algorithms and functions that appear to do the same processes and functions as the human brain using data. This is done by creating patterns that can eventually make decisions based off of the set of algorithms put into play. With knowledge of deep learning, professional can use machines in combination with artificial intelligence creating the ability for the system to learn unsupervised with unstructured or unlabeled data. This opens up a world of possibilities in the world of technology, driving the creation of newer and better running continued learning systems. There are even ways that professionals can integrate knowledge learned from platforms online such as social media and search engines allowing AI system to function and learn on their own. This is done through applications like cloud computing, where big data is used and analyzed to create self-learning systems. Advances in technology have given these systems even larger abilities, creating some AI systems that can process much more data than any human ever could. This can be done by the system using a combination of photos,sounds, and text; using these to learn and integrate into future output. Professionals need to develop several layers in a network known as a neural network, paying close attention to each layer and its architecture and construction.

 

For the last two decades, there has been a sharp increase seen in deep learning systems, some able to accurately identify several that could bemearly impossible for the human eye. Increase in the power and demand is occurring at the same rate as advancements in technology, creating a large need for new and knowledgeable trained employs.

All of the most important industries around the world are counting on this technology; including Aerospace and Defense and Medical Research. Industry leaders are now working to create mechanisms that need no human contact in order to function. This has improved the current specialized technologies used in practices, bringing new hope to cancer research and new insights to the safety of transportation. The same technology and methods used are also integrated into cell phones andnew popular home devices like Alexa and Google. Those that are interested in this exciting and innovative constantly evolving skill are here at the perfect time, as demand increases but, will need to first prepare and grow their knowledge and skill. The Deep Learning Nanodegree Program from Udacity is a self-paced course that normally takes around 4 months to complete.  We will go over the course, reviewing the curriculum and perks, giving those interested in a career change or starting a career in AI all the information to decide if this course is right for them.

 

The Udacity Name

Udacity is famously known for producing graduates that are ready to go out and dominate the job market. The academy has reported that 84% of graduates found a better job within six months of graduation andon average, many saw a salary increase of $24,000 per year. Not only do the numbers create a good name for the academy butalso its reputation for bringing education to anxious learners around the world at an affordable price; the exact reason Udacity was founded. Started by 2 Stanford professors, the academy originally charged nothing with the goal of bringing knowledgeable instruction about programming to learners around the globe. Today, the academy has several programs including Nanodegree programs and many perks to go along with them, all dealing with the world if IT

 

Udacity Deep Learning Nanodegree Review Perks

Apart from instruction and curriculum the course also offers perks to learners and graduates; keeping the success of the students as their top priority. These parks are included in every manner degree program and consist of:

 

Comprehensive Hands-On Projects

These projects are developed in collaboration with leaders in the industry to give students ahands-on andreal-world example. During this project, learners will be prompted to apply what they have learned throughout the duration of the course, using skills and creative thinking to develop solutions to problems companies are facing today.  This project is then reviewed by Udacity staff ensuring that skills were executed properly and functions are up to par with what leaders in the industry are looking for. Successful completion of these projects will give learners their first project to add to their portfolio.

 

Knowledgeable Mentor

Learners make their way through advanced Python training, NumPy training, and more complex AI concepts.Mentors will be there cheering learners on, helping them compete tasks within the expected time.  Mentors are required to have knowledge in the topic areas involved in the course, receiving deep learning courses with advanced Python training themselves. Several of the mentors have taken courses in the past and can answer any questions or problems that learners may have.

 

Flexible schedule

Though it is recommended by Udacity professional to finish in 4 months, learners are able to take all the time they need in order to successfully complete the curriculum. This is perfect for those that already have a career and are wanting to make a change. To complete the course in the recommended time, the academy estimated learners will only have to dedicate 10 hours per week,depending on person it is a good starting point in order to suit each individual need.

 

Instructions 

Besides this, the course is also known for its knowledgeable instructors, many of them years of experience. These inspectors will lead lectures, guiding learners through all of the concepts with detailed explanations and real examples. The instructors for this course include:

 

Mat Leonard – Physicist and Research Neuroscientist

Luis Serrano – Machine Learning Engineer at Google

Cezanne Camacho – Electrical Engineer from Stanford University

Why should learners choose this course?

All the fundamentals of deep learning are covered in this course. Learners get to study and practice all of the newest and most used topics in the fields of deep learning. Complex TensorFlow Python course projects are built using the most up-to-date platforms on the market.  These concepts and more are what you learn throughout the course, with experts there to guide learners, enhancing their knowledge to become competitive. With successful completion of the course, graduates will be able to join teams working on innovative projects that will evolve current AI technology.

 

Demand for this job has skyrocketed and those with strong foundation and experience are able to enter into new companies with an average salary around $146,000 per year. According to artificial intelligence news the last year showed a 344% increase in the demand for jobs  making it the perfect time to start learning. Completing this course will give learners a great foundation to continue learning the more detailed and in-depth topics required to create levels upon levels of neural networks; the inner workings of a successful self-learning machine.

 

Prerequisites and Curriculum

This program is actually suitable for beginners the only prerequisite being a very basic understanding of Python.  Those with a bit of Python training should have no trouble building on to that knowledge learning a more detailed way to use the language to create algorithms. There are 6 total sections throughout the rest of the curriculum, pushing learners right into the deep end with an introduction.

 

Introduction

Starting off with Anaconda and Jupyter notebook training, learners will begin to understand development tools used in order to style transfer their own images.  This is only a very small example that will prepare learners to get ready for diving further into the deep learning course curriculum.

 

 Building Neural Networks

For this part of the course,learners will build their very first network. Instructors introduce the most basic programming tools.  Learners will get insight into how to construct several layers in order to create several completely functioning networks programmed to collect and analyze data. There’s a small hands-on project to complete this section where learners will predict bike-sharing pattern using deep learning course methods taught up to this point.

 

Convolutional neural networks

The next part of the course has an example at the end where learners will work with a dog breed classifier. This is done via an intelligent system which, using algorithms input, can successfully identify the dog breed by analyzing specific features. In this section there is a small look into the deep learning methods of image classification as technology can now recognize faces and certain images based off of patterns. This is taught and applied through concepts like data compression and image denoising, both of which students will get their hands on.

 

Recurrent Neural Network

More intense PyTorch training is part of this section of the course.Here learners will get experience with both long-term and short-term memory networks. They will use this in combination with text to generate words that create a TV script. This section requires a different approach to constructing algorithms, calling learners to create loops and cut offs when needed.

 

 Adversarial Networks

The next 2 sections take learners further into the deep end where the they will start to understand deep convolution generative adversarial networks or GAN. Working to create real life images, this part of the deep learning course consists of creating faces using the concepts introduced in this part of the course in combination with the knowledge learned. This section and the last are among the more difficult sections in the course, but are closer to real-life problems students will encounter in their future jobs.

 

Create a Sentiment Analysis Model

For the last part and perhaps the coolest,students will get to look over new user input using PyTorch sentiment analysis. This part is perhaps the most interactive and informative, learners will not only build a model, but they will also construct a gateway to access it from a website. By this part of the course, learners should expect a bit more advanced PyTorch training and more advanced Python created algorithms. Previous sections will come in handy.

 

Helping Grads Get Hired

When the course is complete,graduates can take advantage of Udacity’s job assistance program. Using this in combination with partnerships with several large companies, Udacity professionals have been able to gain a strong understanding of what employers in the market are looking for. They help new graduates become competitive candidates in the growing job market. There are 3keyways that career services staff help including:

Resume Review

CareerServices professionals will go over the current resume giving feedback on how it could be better. They know exactly what companies are looking for and can help structure the perfect resume for the type of job that is desired. They will also make sure that it’s proofread and ready to send to potential future employers.

 

Interview Prep

Graduates receive preparation on how to conduct a perfect interview. Career Services well hold mock here students will be asked some of the most typical deep learning interview questions, receiving critique on their answers. This will also help graduatesenter into the interview process with confidence as this is one of the most intimidating for new talent going out on the job hunt.

 

Social Profile Review

These days social media is widely used. Almost everyone has some type of account therefore, it is crucial to make sure it’s sending the right message to future employers. With this service,  staff will help learners with their social profiles like LinkedIn, making sure that it is serving them in the best way possible. Graduateswill receive suggestions and have the time to ask any questions in order to effectively creates a profilethat will get them hired.

 

Apart from all of this, learners and graduates can takeadvantage of the Udacity Talent Program.  Recruiters from some of the top companies are swirling around on the hunt for new talent.  Udacity partners with several large names in the business and will skim through employers, matching learners with jobs where their skills are needed. Graduates also have the option to browse through job titles searching for one that they can eventually send their resume to.

Udacity Certificate

A pdf version of the certificate of completion is made available for learners after graduation.  This displays the course name, the students name, and a signature by the Academy’s president. The certificate has been gaining more of a reputation as larger and more reputable companies’ partner with the academy and as more students move up the ladder within the tech job market. This version is printable in order to send to employees or also downloadable to send via email.

Pricing

The academy prices learning access monthly and is normally set at a price of $399 for nanodegree programs. This course is estimated to take 4 months and comes with an offer to pay one total price for 4 months of access totaling $1279. In the case that more time is needed, for each month after the estimated time frame, the monthly fee of $399 will be added.This allows learners to take as long as they need however, drawing on the course longer will drive the price upso learners doneed to be aware and use caution, trying to stick to their expected completion dates as much as possible.

FAQs

Why should you choose a Nanodegree Program?

Udacity is one of the biggest platforms in terms of distance learning and education. It recognized the passion for learning new technologies in some people who were unable to complete their post-graduation due to some issues. Udacity overcame this drawback, implementing some Nanodegree post-graduation programs. Udacity Nanodegree program is meant for distance learning and doesn’t have any age barriers. Anyone who is interested in learning and wants to be a long-term employee in the company.

 

Why learn Deep Learning?

Whether it is a software developer or a fresher, the Deep Learning concept came into consideration in recent years. Deep Learning technology turned into one of the demanded technologies. The researchers and the software professionals are ready to ride the boat for collecting more information on Deep Learning. Deep Learning consists of a model trained and tested based on a huge dataset. It builds a neural network that helps in providing higher accuracy. Due to its wider reach and the most recommended technology, Deep Learning has grabbed the attention of users to scale up their skills.

 

How Udacity Deep Learning Nanodegree program can be helpful from a career perspective?

Deep Learning automates the tasks building models that make predictions based on training sets. These seamless features that Deep Learning serves to act as a helping hand for various sectors. If you have good knowledge about Deep Learning, then it is a jackpot as you can approach any sector, and get yourself hired. Even if you are interested in learning Deep Learning and looking for a noteworthy Deep Learning course, must, you approach Udacity Deep Learning Nanodegree Program. 

 

Who must enroll in Udacity Deep Learning Nanodegree Program?

Although, the course has prerequisites that one must have before enrolling. But this is not the case, even the one with zero knowledge of Deep Learning, Neural Networks can enroll in Udacuty Deep Learning Nanodegree Program. If you have enough Python knowledge and a slight knowledge of Machine Learning, you will enjoy this Nanodegree Program.

 

What concepts can be learned from this Nanodegree Program?

The various Deep Learning algorithms like Supervised Learning, Unsupervised Learning, building testing models, Layering of Neural Networks, measuring the accuracy of the model in terms of loss, and evaluating the structure of the model. The course covers the entire Deep Learning Nanodegree Program with proper practical hands-on knowledge, theoretical concepts explained well, and slight mathematical concepts.

What Grads are Saying

The course rating overall is at a 4.6 out of 5 with nearly 2000 reviews. Most of the difference tends to be a disagreement on depth of the curriculum, with some stating that the tasks are too difficult while others claim they’re too easy. One satisfied review giving the course 5 stars wrote:

 

 

I had enrolled in the course to gain some corporate experience in the Deep Learning domain. Deep Learning is a vast domain converging various concepts, heavy code, a small mathematical concept, etc. After completion of every chapter, the course has designed some projects as assignments. Depending upon the current knowledge about Deep Learning,  you need to build a project. But Udacity offers a wide range of services. In that one service is if you get stuck in between any project, then you can either post the questions in the student community or try to get them reviewed by the expert mentors.”

“It is really awesome. I am in the middle of the course and two companies have contacted me for the job as AI Research Engineer trainee and NLP Engineer. My GitHub profile is really exciting now. It is attracting the recruiters. As a professional i have learnt really the things that gives me the feeling of a next generation engineer. It’s awesome. Please keep up the same Udacity…!” – Amanpreet S.

“I’ve waited until graduating to write this review. For me the journey has been fun and engaging. As an undergrad student I was surprised to find so many people, from very different walks of life, taking the course alongside me. This in itself is a testament to how great the program actually is. They’ve managed to cover almost the entire breadth of topics related to deep learning and neural networks. Earlier weeks focus on building up the fundamentals. Coming up to the last few weeks, I was already pretty comfortable with the topics. I especially loved the lessons they’ve built in collaboration with Ian Goodfellow and Andrew Trask. Initially almost all of the Siraj’s content was horribly frustrating and I was tempted to leave them out. Being a total beginner with neural networks, most of the time. I couldn’t make heads or tails about what the guy was talking about. But after being halfway through the course, the barrier was lifted. Siraj’s video lectures are now one of the most interesting things about this course. As he would say it’s dope!! Most of my time apart from the lessons was spent following up on the links, blogs, articles and videos that the course refers in between the lessons. Before taking this course I was admittedly a novice. I had taken a few online courses related to data science and machine learning but I was missing a lot. Taking this course allowed me to write a winning proposal for 2017’s Google Summer of Code with CERN. I look forward to increasing my skills further by practising and exploration.” – Vyom S.

 

“This is probably the most approachable way to get into deep learning I have found thus far. The course covers a lot of interesting subjects, with (usually) good explanatory videos and walkthroughs. These always feel fresh and get you motivated for the subjects you are about to learn. As a bonus, they have gotten a few known names to present individual subjects. As an example, the introduction to GANs is done by none other than the inventor himself, which is a cool bonus. There is a lot of great material here, and while some of it feels a bit rushed or oversimplified at times, they do reference more material for those that want to dive deeper into the learning B). (That being said, you will definitely have to get your hands dirty at times as well.) The main value here is in the projects and introductory notebooks. Here, you’ll get a lot of hands on experience writing code, and you will definitely feel like you’ve come a long way after finishing them all. Best of all, you’ll have working code that you can tweak and use for your own projects afterwards, and perhaps a ton of ideas as well. All in all, money well spent, at least in my case.” – Peter L.

 

While a 1-star reviewer claimed:

“Doesn’t go deep enough, majority of tasks is just basic programming stuff like juggling lists. Programming assignments are mainly based on initializing variables.” – Sergey B

Final Verdict

 

Udacity’s reputation is growing by day with larger and more reputable companies becoming part of their sponsors more and more. This is the perfect course for professionals that are looking to start a career in deep learning and AI however, this may not be the right course for those with extensive training. The Curriculum bushes the surface of deep learning concepts and goes in a little further to others however, it just depends on the level of the potential learner.

 

There’s no doubt that completing a Nanodegree from Udacity is useful and with several companies on the hunt for new and rising talent,those with skills in deep learning and looking to make a career change can take advantage of the benefits from all the Udacity perks as well as the comprehensive and hands-on experience they will receive, not to mention the job assistance. There really is no better course out there that is as well-rounded as this one, equipped with assistance to make graduates the best and most sought-after candidates to the game changers of IT.

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